TY - GEN
T1 - A Study on Stenosis Detection Based on Non-contact Thrill Wave Imaging and Gradient-Boosting Decision Tree
AU - Shimazaki, Takunori
AU - Kawakubo, Yoshifumi
AU - Iwai, Rumi
AU - Fukuhara, Masashi
AU - Aono, Hiroki
AU - Mitsudo, Jun
AU - Hayashi, Yuhei
AU - Ata, Shingo
AU - Yokoyama, Takeshi
AU - Anzai, Daisuke
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Hemodialysis therapy generally requires a special blood vessel called an arteriovenous fistula (AVF), which is surgically anastomosed between an artery and a vein. Since an AVF often becomes stenosis, palpation is used to palpate the vessel wall vibrations, which is called thrill wave, before and after hemodialysis treatment. This method is widely used, especially in Japan, because of its simplicity. However, several problems in the palpation has been pointed out in terms of reliability because the palpation requires contact diagnosis. In order to solve the problems in the conventional contact palpation, we developed a thrill wave measurement device using non-contact imaging based on an optical technology. Then, we introduced a gradient-boosting decision tree algorithm to detect stenosis in AVFs. The experimental results showed that true positive rate (TPR) = 92.3%, true negative rate (TNR) = 76.7%, false positive rate (FPR) = 7.7% and false negative rate (FNR) = 23.3% to identify normal and stenotic AVFs.
AB - Hemodialysis therapy generally requires a special blood vessel called an arteriovenous fistula (AVF), which is surgically anastomosed between an artery and a vein. Since an AVF often becomes stenosis, palpation is used to palpate the vessel wall vibrations, which is called thrill wave, before and after hemodialysis treatment. This method is widely used, especially in Japan, because of its simplicity. However, several problems in the palpation has been pointed out in terms of reliability because the palpation requires contact diagnosis. In order to solve the problems in the conventional contact palpation, we developed a thrill wave measurement device using non-contact imaging based on an optical technology. Then, we introduced a gradient-boosting decision tree algorithm to detect stenosis in AVFs. The experimental results showed that true positive rate (TPR) = 92.3%, true negative rate (TNR) = 76.7%, false positive rate (FPR) = 7.7% and false negative rate (FNR) = 23.3% to identify normal and stenotic AVFs.
UR - http://www.scopus.com/inward/record.url?scp=85163712494&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85163712494&partnerID=8YFLogxK
U2 - 10.1109/ISMICT58261.2023.10152043
DO - 10.1109/ISMICT58261.2023.10152043
M3 - Conference contribution
AN - SCOPUS:85163712494
T3 - International Symposium on Medical Information and Communication Technology, ISMICT
BT - 2023 IEEE 17th International Symposium on Medical Information and Communication Technology, ISMICT 2023
PB - IEEE Computer Society
T2 - 17th IEEE International Symposium on Medical Information and Communication Technology, ISMICT 2023
Y2 - 10 May 2023 through 12 May 2023
ER -